SMT-based Verification of LTL Specifications with Integer Constraints and its Application to Runtime Checking of Service Substitutability

An important problem that arises during the execution of service-based applications concerns the ability to determine whether a running service can be substituted with one with a different interface, for example if the former is no longer available. Standard Bounded Model Checking techniques can be used to perform this check, but they must be able to provide answers very quickly, lest the check hampers the operativeness of the application, instead of aiding it. The problem becomes even more complex when conversational services are considered, i.e., services that expose operations that have Input/Output data dependencies among them. In this paper we introduce a formal verification technique for an extension of Linear Temporal Logic that allows users to include in formulae constraints on integer variables. This technique applied to the substitutability problem for conversational services is shown to be considerably faster and with smaller memory footprint than existing ones

Evorus: A Crowd-powered Conversational Assistant Built to Automate Itself Over Time

Crowd-powered conversational assistants have been shown to be more robust than automated systems, but do so at the cost of higher response latency and monetary costs. A promising direction is to combine the two approaches for high quality, low latency, and low cost solutions. In this paper, we introduce Evorus, a crowd-powered conversational assistant built to automate itself over time by (i) allowing new chatbots to be easily integrated to automate more scenarios, (ii) reusing prior crowd answers, and (iii) learning to automatically approve response candidates. Our 5-month-long deployment with 80 participants and 281 conversations shows that Evorus can automate itself without compromising conversation quality. Crowd-AI architectures have long been proposed as a way to reduce cost and latency for crowd-powered systems; Evorus demonstrates how automation can be introduced successfully in a deployed system. Its architecture allows future researchers to make further innovation on the underlying automated components in the context of a deployed open domain dialog system.Comment: 10 pages. To appear in the Proceedings of the Conference on Human Factors in Computing Systems 2018 (CHI'18

Customer-engineer relationship management for converged ICT service companies

Thanks to the advent of converged communications services (often referred to as ‘triple play’), the next generation Service Engineer will need radically different skills, processes and tools from today’s counterpart. Why? in order to meet the challenges of installing and maintaining services based on multi-vendor software and hardware components in an IP-based network environment. The converged services environment is likely to be ‘smart’ and support flexible and dynamic interoperability between appliances and computing devices. These radical changes in the working environment will inevitably force managers to rethink the role of Service Engineers in relation to customer relationship management. This paper aims to identify requirements for an information system to support converged communications service engineers with regard to customer-engineer relationship management. Furthermore, an architecture for such a system is proposed and how it meets these requirements is discussed

A monitoring approach for runtime service discovery

Effective runtime service discovery requires identification of services based on different service characteristics such as structural, behavioural, quality, and contextual characteristics. However, current service registries guarantee services described in terms of structural and sometimes quality characteristics and, therefore, it is not always possible to assume that services in them will have all the characteristics required for effective service discovery. In this paper, we describe a monitor-based runtime service discovery framework called MoRSeD. The framework supports service discovery in both push and pull modes of query execution. The push mode of query execution is performed in parallel to the execution of a service-based system, in a proactive way. Both types of queries are specified in a query language called SerDiQueL that allows the representation of structural, behavioral, quality, and contextual conditions of services to be identified. The framework uses a monitor component to verify if behavioral and contextual conditions in the queries can be satisfied by services, based on translations of these conditions into properties represented in event calculus, and verification of the satisfiability of these properties against services. The monitor is also used to support identification that services participating in a service-based system are unavailable, and identification of changes in the behavioral and contextual characteristics of the services. A prototype implementation of the framework has been developed. The framework has been evaluated in terms of comparison of its performance when using and when not using the monitor component

Access to recorded interviews: A research agenda

Recorded interviews form a rich basis for scholarly inquiry. Examples include oral histories, community memory projects, and interviews conducted for broadcast media. Emerging technologies offer the potential to radically transform the way in which recorded interviews are made accessible, but this vision will demand substantial investments from a broad range of research communities. This article reviews the present state of practice for making recorded interviews available and the state-of-the-art for key component technologies. A large number of important research issues are identified, and from that set of issues, a coherent research agenda is proposed

An illustrative recovery approach for stateful interaction failures of orchestrated processes

During a stateful interaction, a partner service may become unavailable because of a server crash or a temporary network failure. Once the failed service becomes available again, the interaction partners do not have any knowledge about each other’s state, possibly resulting in errors or deadlocks. This paper proposes an approach to the recovery of stateful interactions based on service interaction patterns and process transformations. Our recovery approach works without a central management node and without additional communication protocols. We also minimize the changes to the description of the service supported by the recovery-enabled process. Our approach allows one partner process to be modified in order to support failures in a way that interaction with the other (unchanged) processes is still possible

Evaluating Conversational Recommender Systems via User Simulation

Conversational information access is an emerging research area. Currently, human evaluation is used for end-to-end system evaluation, which is both very time and resource intensive at scale, and thus becomes a bottleneck of progress. As an alternative, we propose automated evaluation by means of simulating users. Our user simulator aims to generate responses that a real human would give by considering both individual preferences and the general flow of interaction with the system. We evaluate our simulation approach on an item recommendation task by comparing three existing conversational recommender systems. We show that preference modeling and task-specific interaction models both contribute to more realistic simulations, and can help achieve high correlation between automatic evaluation measures and manual human assessments.Comment: Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '20), 202

Context constraint integration and validation in dynamic web service compositions

System architectures that cross organisational boundaries are usually implemented based on Web service technologies due to their inherent interoperability benets. With increasing exibility requirements, such as on-demand service provision, a dynamic approach to service architecture focussing on composition at runtime is needed. The possibility of technical faults, but also violations of functional and semantic constraints require a comprehensive notion of context that captures composition-relevant aspects. Context-aware techniques are consequently required to support constraint validation for dynamic service composition. We present techniques to respond to problems occurring during the execution of dynamically composed Web services implemented in WS-BPEL. A notion of context { covering physical and contractual faults and violations { is used to safeguard composed service executions dynamically. Our aim is to present an architectural framework from an application-oriented perspective, addressing practical considerations of a technical framework

Sistema de Sugestões Sensível ao Contexto

Over the last few years, pervasive systems have experienced some interesting development. Nevertheless, human-human interaction can also take advantage of those systems by using their ability to perceive the surrounding environment. In this dissertation, we have developed a pervasive system - named ConversationaL Aware Suggestion SYstem (CLASSY) - which is aware of the conversational context and suggests the users potentially useful documents or that, somehow, save time executing a specific task. We have also proposed two different approaches - the Neighborhood one, that uses semantic similarity, based on proximity data in order to classify the relationship between tokens; and the Reinforcement Learning one, that uses implicit feedback associated with each suggestion as a source of knowledge that can be used to improve the system's performance over time. The conducted tests showed that these two approaches not only enhanced the pervasive behavior of the system, but also increased its global performance. A case study regarding the importance of feedback on context-limited environments was also carried out, whose results showed that it is still a useful source of knowledge regardless the conversational environment's characteristics.Ao longo dos últimos anos, os sistemas pervasivos têm sido fonte de um grande desenvolvimento. Contudo, as interações humano-humano também podem tirar vantagem deste tipo de sistemas recorrendo à sua capacidade para entender o ambiente que o rodeia. Nesta dissertação, foi desenvolvido um sistema pervasivo - chamado Sistema de Sugestões Sensível ao Contexto (CLASSY) - que está consciente dos vários contextos conversacionais e que sugere documentos considerados potencialmente úteis para os utilizadores ou que, de alguma forma, poupam tempo na execução de uma tarefa específica. Foram também propostas duas aproximações diferentes - a de vizinhança, que usa similaridade semântica, baseando-se em proximidades de forma a classificar relações entre palavras; e a de Aprendizagem por Reforço, que usa feedback implícito dos utilizadores associado a cada sugestão, como fonte de conhecimento que pode ser utilizado para melhorar a performance do sistema ao longo do tempo. Os testes realizados mostraram que as aproximações acima referidas melhoraram não só o comportamento pervasivo do sistema, mas também a sua performance global. Foi, ainda, analisado um caso de estudo referente à importância de feedback em ambientes com contexto limitado, onde os resultados mostraram que o mesmo continua a ser uma importante fonte de conhecimento, independentemente das características do ambiente conversacional.Mestrado em Engenharia de Computadores e Telemátic

Adaptive Process Management in Cyber-Physical Domains

The increasing application of process-oriented approaches in new challenging cyber-physical domains beyond business computing (e.g., personalized healthcare, emergency management, factories of the future, home automation, etc.) has led to reconsider the level of flexibility and support required to manage complex processes in such domains. A cyber-physical domain is characterized by the presence of a cyber-physical system coordinating heterogeneous ICT components (PCs, smartphones, sensors, actuators) and involving real world entities (humans, machines, agents, robots, etc.) that perform complex tasks in the “physical” real world to achieve a common goal. The physical world, however, is not entirely predictable, and processes enacted in cyber-physical domains must be robust to unexpected conditions and adaptable to unanticipated exceptions. This demands a more flexible approach in process design and enactment, recognizing that in real-world environments it is not adequate to assume that all possible recovery activities can be predefined for dealing with the exceptions that can ensue. In this chapter, we tackle the above issue and we propose a general approach, a concrete framework and a process management system implementation, called SmartPM, for automatically adapting processes enacted in cyber-physical domains in case of unanticipated exceptions and exogenous events. The adaptation mechanism provided by SmartPM is based on declarative task specifications, execution monitoring for detecting failures and context changes at run-time, and automated planning techniques to self-repair the running process, without requiring to predefine any specific adaptation policy or exception handler at design-time